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By G. D. Naugle

Deep open-pit mines invariably affect the local and regional hydrologic systems. Pit dewatering, occurring during mining operations, puts an obvious hydrologic stress on these hydrologic systems. However, post-mining hydro-logic impacts resulting from the pit refilling with ground water following the cessation of mining activity can also be significant. Prediction of the rate at which the post-mining pit will fill with ground water is a critical aspect of assessing such long-term hydrologic impacts. Numerical ground-water flow modeling prov1des a method that can be used to predict the rate at which pits will fill with ground water.

Jan 1, 1992

By J. H. Tu

The technical paper correctly points out that the kriging variance is not a good measure of the uncertainty of the estimated (i.e., kriged) value of individual blocks. The authors claim that their proposed jack-knife method, which is a rekriging of each block by eliminating, in turn, one sample from m the original sample set and then taking the average of the rekriged estimates, not only gives good block estimates, but the resulting jackknife kriging standard deviation is a useful indicator of the "true uncertainty associated with block estimates." However, they immediately abandon the idea of using the block-by-block standard deviations, reasoning that these standard deviations are not independent and that there is no easy way to utilize them. There may be another reason for not using them. The jackknife standard deviations for individual blocks given in their example are mostly in the range of 0.004 to 0.005 oz/st (0.14 to 0.17 g/t) with only one block having a high value of 0.012 oz/st (0.41 g/ t). These individual block standard deviations are as low as the jackknife standard deviation for the mean grade of the entire shape, i.e., 0.0041 oz/st (0.14 g/t). Do they represent the "true uncertainty" .of the individual block estimates? Could the authors explain this? In a global shape consisting of a large number of blocks, any given sample will affect the kriged estimate of only those few blocks within its vicinity. This is the rationale for the authors' selective rekriging, making the jackknife algorithm more efficient. On second thought, why not do away with jackknifing altogether? Just cumulate and normalize, if necessary, the kriging weights of each sample used during the ordinary block kriging process, and then compute the global variance from these kriging weights and their respective sample grades? After all, isn't the global mean grade nothing but the weighted average of the samples used in the estimation? Reply by G.S. Adisoma and M.G. Hester The jackknife is one of the many tools in a practitioner's toolbox to solve estimation problems. The strengths of the technique lies in its simplicity, i.e., it uses the concept of mean and standard deviation and the fact that it can be easily combined with other tools, in this case kriging. Because the jackknife kriging (JK) estimate is also the mean of the pseudovalues, the JK standard deviation is attractive just as the standard deviation of the mean explains the variability of the data. The difference is that the pseudovalue calculation in jackknife kriging uses the ordinary kriging (OK) weighting scheme instead of simple arithmetic averaging. The data used to illustrate the jackknife technique in the paper con¬sist of high values that are roughly three times the low values. The resulting JK estimate of the block grades show that the highest estimate is roughly twice the grade of the lowest estimate. The contrast between the low and the high estimate is more evident in the JK estimate than in the OK estimate, even though the mean grades of the blocks for the two estimates are very similar. Nonetheless, in this paper, we are concentrating more on the need for a more realistic measure of uncertainty, or precision, for the estimate. Unlike its OK counterpart, the JK standard deviation of the blocks clearly reflects the original data variation. The highest JK standard deviation of the blocks is three times its lowest value. This follows our intuition that, when the samples used to estimate a block is more variable, the resulting estimation variance (or standard deviation) should be higher than the case where the samples are more uniformly valued. However, block-by-block standard deviation or variance is of little practical value in reserve estimation and classification, as well as in mine planning. One is usually more interested in quantifying not the variance of the individual block estimate, but the uncertainties associated with a much larger dimension, such as the minable reserve. Thus, the thrust of the paper is to find a simple way to obtain a single estimation variance or standard deviation associated with the reserve grade estimate. The discussion by J.H. Tu did not mention how one would obtain the global variance from the OK weights and the sample grades. As a technique that offers a data value-based measure of uncertainty for its estimate, the "leave-one-out" jackknife fills this need nicely through the block kriging shortcut approach described in the paper. Note: The first column and the last two columns of Table 3 in the paper should have contained a single number each, namely, an OK estimate of 0.0317, a JK estimate of 0.0333 and a JK standard deviation of 0.0041 oz/st, respectively, for the shape, as are obvious from the text.

Jan 1, 1997

By J. H. Tu

The technical paper correctly points out that the kriging variance is not a good measure of the uncertainty of the estimated (i.e., kriged) value of individual blocks. The au thors claim that their proposed jackknife method, which is a rekriging of each block by eliminating, in turn, one sample from the original sample set and then taking the average of the rekriged estimates, not only gives good block estimates, but the resulting jackknife kriging standard deviation is a useful indicator of the "true uncertainty associated with block estimates." However, they immediately abandon the idea of using the block-by-block standard deviations, reasoning that these standard deviations are not independent and that there is no easy way to utilize them. There may be another reason for not using them. The jackknife standard deviations for individual blocks given in their example are mostly in the range of 0.004 to 0.005 oz/st (0.14 to 0.17 g/t) with only one block having a high value of 0.012 oz/st (0.41 g/ t). These individual block standard deviations are as low as the jackknife standard deviation for the mean grade of the entire shape, i.e., 0.0041 oz/st (0.14 g/t). Do they represent the "true uncertainty" of the individual block estimates? Could the authors explain this? In a global shape consisting of a large number of blocks, any given sample will affect the kriged estimate of only those few blocks within its vicinity. This is the rationale for the authors' selective rekriging, making the jackknife algorithm more efficient. On second thought, why not do away with jackknifing altogether? Just cumulate and normalize, if necessary, the kriging weights of each sample used during the ordinary block kriging process, and then compute the global variance from these kriging weights and their respective sample grades? After all, isn't the global mean grade nothing but the weighted average of the samples used in the estimation? Reply by G.S. Adisoma and M.G. Hester The jackknife is one of the many tools in a practitioner's toolbox to solve estimation problems. The strengths of the technique lies in its simplicity, i.e., it uses the concept of mean and standard deviation and the fact that it can be easily combined with other tools, in this case kriging. Because the jackknife kriging (JK) estimate is also the mean of the pseudovalues, the JK standard deviation is attractive just as the standard deviation of the mean explains the variability of the data. The difference is that the pseudovalue calculation in jackknife kriging uses the ordinary kriging (OK) weighting scheme instead of simple arithmetic averaging. The data used to illustrate the jackknife technique in the paper consist of high values that are roughly three times the low values. The resulting JK estimate of the block grades show that the highest estimate is roughly twice the grade of the lowest estimate. The contrast between the low and the high estimate is more evident in the JK estimate than in the OK estimate, even though the mean grades of the blocks for the two estimates are very similar. Nonetheless, in this paper, we are concentrating more on the need for a more realistic measure of uncertainty, or precision, for the estimate. Unlike its OK counterpart, the JK standard deviation of the blocks clearly reflects the original data variation. The highest JK standard deviation of the blocks is three times its lowest value. This follows our intuition that, when the samples used to estimate a block is more variable, the resulting estimation variance (or standard deviation) should be higher than the case where the samples are more uniformly valued. However, block-by-block standard deviation or variance is of little practical value in reserve estimation and classification, as well as in mine planning. One is usually more interested in quantifying not the variance of the individual block estimate, but the uncertainties associated with a much larger dimension, such as the minable reserve. Thus, the thrust of the paper is to find a simple way to obtain a single estimation variance or standard deviation associated with the reserve grade estimate. The discussion by J.H. Tu did not mention how one would obtain the global variance from the OK weights and the sample grades. As a technique that offers a data valuebased measure of uncertainty for its estimate, the "leave-one-out" jackknife fills this need nicely through the block kriging shortcut approach described in the paper. Note: The first column and the last two columns of Table 3 in the paper should have contained a single number each, namely, an OK estimate of 0.0317, a JK estimate of 0.0333 and a JK standard deviation of 0.0041 oz/st, respectively, for the shape, as are obvious from the text. ?

Jan 1, 1998

By G. S. Austin, L. A. Brandvold, J. Renault

A series of tests were run on soil samples collected near the site of a Socorro, NM lead smelter that was abandoned more than 98 years ago. Three 30.5- x 30.5-m (100-X 100-ft) squares provided 13 samples each. As described in Part I (this issue), each sample was divided into seven splits according to particle size. A mineralogical examination of the fine-size fraction of Pb-contaminated soils failed to reveal crystalline Pb compounds. These authors conclude that Pb is present as amorphous phases or is adsorbed on the surfaces of soil particles. Site vegetation contained elevated Pb levels that increased with increasing Pb amounts in the soil. However, the biological absorption coefficient (BAC) indicates that some of the site's Pb is unavailable, or the plants are able to limit their uptake. Of the vegetation tested, rabbit bush showed the greatest increase of Pb levels in its roots, whereas levels in creosote were highest in the foliage. In cactus, the Pb levels varied. The amount of Pb due to dust incorporated in plant tissue is almost negligible compared to the amount absorbed through the plant vascular system.

Jan 1, 1994

By T. P. Meloy

Media mills operate by having energy transferred to the media which in turn grinds the feed material in a packed bed. Regardless of the mill type, the media energy density per unit surface area is constant. Since for optimum grinding conditions, both peak pressures and particle number of the bed depth are constant, the frequency of energy input is inversely proportional to feed size. As the particle size decreases the voles energy density increases linearly necessitating cooling in stirred mills. Grinding finer particles therefore, requires moving from rotary to vibratory mills, and the finest, the stirred mills.

Jan 1, 1987

By K. S. Venkataraman

The physical properties of clay-water systems depend on the complicated system of forces between the clay particles themselves, and between the clay particles and the ions in the liquid phase. The kind and distribution of ions in, on, and between the clay particles and the size and the shape of the particles are the basic factors determining the macroscopic behavior of clay-water systems. Understanding the system requires a knowledge of the nature of the clay particles, their size, structure, composition, and surface properties, and of the manner in which they interact with ions [and molecules] in the surrounding liquid [or other medium]. The validity of Professor Brindley's words (Brindley, 1958), written three decades ago in the context of making pottery, whitewares, and electrical porcelains, transcends time, and the basic message is perhaps all the more important in the considerably expanded use of ceramics for structural, thermal, tribological, electronic, and other applications. Silicon carbide, silicon nitride, and sialons have been studied in the last two decades for high- temperature structural and tribological applications, particularly for using in internal combustion engines. Titanates, zirconates and niobates of barium, strontium and lead, have high dielectric constants, and are extensively used in the formulations for making capacitors. Hexagonal ferrites (molecular formula MO.6Fe2O3) are in use for making permanent magnets for fabricating miniature motors, and for assembling loud speakers, particle accelerators etc. Cubic ferrites such as magnesium-zinc ferrite and nickel-zinc ferrite are used as transformer cores, and for other high-frequency applications. In this context, Richerson's recent book (Richerson, 1984) on the general scope of traditional and technical ceramics is a good starting point for an overview of contemporary ceramics technology. Glasses are a whole class of amorphous materials used widely as sintering aids, and for making glass-bonded ceramics and glass-ceramic composites. Composites are yet another burgeoning field where two or more particulate components are used for improving the performance of ceramics. For all these applications, the inorganic starting materials are almost always submicron and near-micron powders. Understanding the powders' physicochemical properties, and their surface chemical interactions with the surrounding liquid/gaseous medium is-necessary for making reliable ceramic parts at competitive prices. Even though ceramics science and engineering has attained its separate identity in universities and the industry, ceramists themselves would concede that ceramics science is a cross-disciplinary field, having incorporated and assimilated within itself many principles from several apparently disjointed disciplines. Principles of material science, graduate-level physics and chemistry, polymer science, surface and colloid chemistry, transport phenomena, particle technology, unit operations commonly used in chemical engineering and mineral processing, and statistics and applied mathematics are integral part of any ceramics curriculum in universities. Added to this is the fact that all bench-scale successes in making ceramic parts are to be scaled-up for larger throughput operations. Understanding and applying process engineering principles of comminution, classification, drying, calcination, etc. then becomes essential. CERAMIC FORMING: Despite the diversity of the materials and processes, conceptually, the steps involved in making ceramic parts have remained the same over several decades: The different components for making the pan (usually one or more powders plus other forming and sintering additives) are proportioned and mixed thoroughly, and the well-mixed formulations are consolidated into desirable shapes known as "green bodies." Usually binders such as wax, clay, organic polymers and surfactants, whether dispersed or dissolved in a suitable liquid are used during mixing the batch for giving strength for the green bodies. In the dried green state, the inorganic powders typically occupy only 55 to 60% of the bulk volume of the body, depending on the particle size distributions of the powders and the forming history, with mostly inter- particle voids accounting for the rest of the void volume. SINTERING: The formed bodies are then fired in high- temperatures kilns/furnaces during which the parts are exposed to a predetermined temperature profile, and "soaked" for a certain duration at the final high temperatures, typically between 1200 K and 1900 K, and then cooled to room temperature. The gaseous atmosphere in the furnace is controlled (oxidizing, reducing, or inert) when necessary. During the initial stages of firing, volatile liquids evaporate, and during the intermediate temperatures between 400 and 600 K, the the organic polymeric additives pyrolize and oxidize into water vapor, CO, C02, and other gases. At still high temperature, the glasses, when present, soften, and simultaneously, the ceramic particles rearrange into a network of grains with definite grain boundaries so as to reduce the total interfacial free

Jan 1, 1990

By S. Kemball-Cook, D. Heinze, A. Kornberg, M. Harmon

Climate change presents risks to mine infrastructure, operations and long-term obligations to protect environmental conditions. Management strategies and design of infrastructure and containment systems based on past or current climate conditions may be inadequate in the future if changes in climate are not taken into account in planning for mine operations, decommissioning, closure and post-closure. Data-driven assessments using climate model projections of the future can be used to quantify: • Changes in site-specific risks to mine structures, access, containment facilities, operations and staff safety. • Changes in vegetation and water balance/chemistry, and potential for acid mine drainage, erosion and design failure. Climate- and weather-related risks are a serious threat to the mining industry, but risk transfer solutions can alleviate these vulnerabilities. Mining companies can protect themselves through bespoke solutions which provide operators, investors and buyers with protection against weather-related disruptions to operations by hedging to smooth revenues. Using risk transfer structures to mitigate climate risks is a mechanism that is available to all types of mining operations world-wide. In this paper, we describe methods for evaluating site-specific climate change impacts and developing risk transfer solutions to mitigate their effects. EVALUATING MINE RISKS FROM CLIMATE CHANGE The best available tool for understanding potential future changes to the earth’s climate system are global climate models (GCMs) (IPCC, 2014). GCMs are computer simulations of the climate system which include the atmosphere, ocean, land surface, cryosphere and biosphere. Because of the computational demands of running a global model for many decades, the spatial resolutions of the GCM grids are necessarily coarse, typically on the order of 100-300 km. GCM data are therefore suitable for evaluating future physical risks on global or continental scales, but may not be appropriate for evaluating location-specific risks (e.g. Kotamarthi et al., 2016). For site-specific, quantitative physical risk assessment, GCM projection data are “downscaled” or adapted for use at the local level using statistical techniques together with observed data (statistical downscaling) or using high-resolution regional climate models (RCMs) that focus on a single geographic region and have spatial resolutions of 10-50 km (dynamical downscaling). Downscaling bridges the gap between the GCM scale and regional/local scale. Through the downscaling process, new information is added to the GCM output from observations and/or RCMs, resulting in patterns for weather variables that are more consistent with local terrain and weather influences. Downscaled climate change projections for the mine site are selected considering mine location and geography, the availability of local observations, and the performance of the downscaling method and global/regional models used to develop the projection in simulating the variable under study. Where possible, we use projections from an ensemble of global and regional model runs spanning a range of future greenhouse gas (GHG) scenarios.

Jan 1, 2019

By G. E. Jones, G. K. Hoffman

Two Sun Juan Basin studies were completed through the USGS National Coal Availability program. The study areas are in the northwest Bisti field (Fruitland Formation) and in the eastern Standing Rock field (Menefee Formation). In the Bisti and Standing Rock areas, the original coal resource5 are estimated at 4.66 and 3.1 7 Gt (5.14 and 3.49 billion st), respectively. The Bisti coal resources are greatly reduced by the Bisti-De-Nu- Zin wilderness area, which contains an estimated 1.13 Gt (1.25 billion st) of coal. Technological restrictions remove 32.5% from Standing Rock's original resource. Available resources are 60%. 2.79 Gt (3.07 billion st), of the Bisti original resource and 65%, 2.07 Gt (2.28 billion st), of the original Standing Rock resource.

Jan 1, 2002

By Anders Sellgren, K. Hansson, A. Jedborn

In the mining industry, conversion of fine particles into a slurry is often part of the normal processing of the ore. Therefore. from a system's point of view, slurry transportation would be considered as a natural alternative, all the way from the working face to the final processing. In underground mines, there is sometimes a considerable inflow of ground water that has to be pumped out. When the mine dewatering installations are integrated with a hydraulic hoisting system, the cost of power needed to pump out the ground water can be excluded from the cost of hoisting, compared with other modes of transporting the solids to the surface. The chief advantage of hydraulic hoisting is that the hoisting capacity can be increased at comparatively low total cost without necessitating the sinking of new shafts. Alternative examples include deepening of the existing mechanical hoisting system, truck, or conveyor belts transport in ramps to the present level. These often become very expensive. The economic effectiveness of hydraulic hoisting and hydraulic design considerations have been discussed by Kostuik (1965) and Sellgren (1985, 1986) for both small shallow mines and large deep underground mines. Objective and scope The objective of this study was to demonstrate the feasibiliy of hydraulic hoisting in hypothetical examples of mine deepening. Underground grinding to a maximum particle size of about 700 um (about 25 mesh) is considered. The pumping of ground ore products with positive displacement plunger or membrane type of pumps at working pressures of up to 15 MPa (2200 psi) is a thoroughly tested technique (Venton, 1986). Hydraulic hoisting system A hydraulic hoisting system is described schematically in Fig. 1. The ore is mined, handled, and crushed conventionally. It is then ground wet underground. The slurry is then temporarily stored in an agitated tank and pumped to an agitated receiving tank on the surface. The ore is then further processed in the concentrator. The capacity of a pipeline is very high. For example, an annual production of 500 Kt (550,000 st) of ore can be handled in a 100-mm-diam (4-in.-diam) pipeline. Systems layout - economic effectiveness Schematic mine layouts are presented that represent situations where hydraulic hoisting often is the most economical alternative. A situation where the ore is trucked to the level of the existing hoisting system is shown in Fig. 2 (following page). With hydraulic hoisting, only a shaft for ventilation, pipe- line, and personnel are needed. In a first phase (Fig. 2). a hydraulic hoisting installation with crushing and grinding units, storage facilities, and pumps has been located at a level of about 400 to 600 m (1310 to 1970 ft) below the surface. With further development of the mine, the hydraulic hoisting

Jan 1, 1990

By J. P. Fitzgerald

This paper is an accumulation of information on the geology, mineralogy and mining of the Hectorite clay deposit owned by NL Chemicals (U.S.A.), Inc. The mine is located in San Bernardino County, California approximately 35 miles east of Barstow and 1-1/2 miles south of U.S. Highway 40. The region is known as the Mojave Block which is a region bound by the San Andreas fault zone to the southeast and the Garlock fault zone to the North. The faults of both zones are active, vertical faults along which movements are mainly horizontal. Most of the faults within the Mojave Block are high angle faults which trend northwest. They are considered part of the San Andreas fault system and are a result of the right- lateral movement characteristic of this system. The east-trending faults are also high angle faults, along which movement has displaced rock units vertically. Manix fault is the only mapped fault that shows evidence of left slip which is characteristic of the Garlock sys tem to the North.

Jan 1, 1986

By H. W. Renner

The paper industry is an $80 billion/year business that is the largest consumer of industrial minerals. Paper industry generally refers to paper and paperboard products, including pulp mills. Grades and uses of paper and paperboard are very diverse, including such things as napkins, paper plates, corrugated boxes, magazines, newsprint, currency, and copier paper. Only about 40% of paper utilizes industrial minerals as fillers or coating materials. Minerals are used for both functional and economic reasons. Most often, minerals such as kaolin clay and calcium carbonate are used to improve print quality, brightness and opacity of paper. The minerals can be added as fillers into the paper in the wet end of the papermaking system, or can be applied as part of a coating to the paper. Coated papers are the highest quality paper, being used for magazines, advertising brochures and annual reports. Common uses for filled uncoated paper are books, copier paper, envelopes and many of the Sunday newspaper advertising inserts.

Jan 1, 1993

By Kenneth L. Clifford

We have heard a lot during the recession about the mining industry now competing in a world market for sales of such commodities as copper, lead, zinc, molybdenum, iron ore, and phosphate. If the US mining industry is to survive, do we not have to reduce direct operating costs to a minimum? How significant is labor cost compared to consumables, electricity, fuel, maintenance, materials, and transportation? Ore grade is ultimately the dominant factor; but can we offset its dominance by improving productivity? Is the US mining industry perhaps only 25-30% as productive as it might be? What prevents the industry from being more productive? Can we retrofit older plants to be more productive or does it take a new plant with the largest equipment available for each unit operation? Present Productivity A copper industry study a few years ago covering 13 US copper concentrators ranging from about 10-45 kt/d (11,000-50,000 stpd) showed that productivity did not vary with capacity above 18 kt/d (20,000 stpd). Operating productivity varied significantly, however, from about 180-635 t/d (200-700 stpd) per operating hourly worker in most units, but one operation had 900 kt/d (1,000 stpd). Concentrators with more than 545 t/d (600 stpd) per hourly worker were in the 23 kt/d (25,000 stpd) or more category. Maintenance productivity covered about the same range, but most concentrators were in the 270¬635 t/d (300-700 stpd) per hourly maintenance worker. Again, one company stood well above others by exceeding 1 kt/d (1,100 stpd). Total hourly productivity ranged from 125-280 t/d (140-310 stpd) per hourly worker for most concentrators. The company with the most productive operation, however, was above 455 t/d (500 stpd). Salaried worker productivity for most operations was in the 725 t/d to 1.2 kt/d (800-1,300 stpd) per salaried worker range. The best operation was 2.2 kt/d (2,400 stpd). The end result is, of course, tons per day per total personnel. Most operations fell in the 110-220 t/d (120-240 stpd) range with the best operation at 400 t/d (440 stpd). This is the productivity definition that is most directly related to unit costs. Many of these operations have made some productivity progress

Jan 11, 1983

By James R. Miller

This paper will describe the balling disc operation of the Marcona Mining Company at San Nicolas, Peru, with special reference to green ball quality. The report covers experience during the period of September and October 1965 and will be, more a state-of-the-art at Marcona report rather than -a technical treatise.

Jan 1, 1966

By A. L. Ling, A. K. Janzen

"Design of effective mine water treatment plants depends on the ability to reliably predict treatment outcomes, but systems with multiple chemical and physical treatment processes and recycle loops can be difficult to model. GoldPHREEQC is a modeling framework that integrates mass and flow routing capabilities of GoldSim software and water quality calculations provided by PHREEQC, and is well-suited to modeling parameters of interest in the mining industry, especially metals and sulfate. Physical processes such as membrane separation and greensand filtration are modeled by defining mass rejections for each parameter and flow routing based on vendor projections and bench- or pilot-scale equipment testing. GoldPHREEQC models chemical precipitation processes such as HDS metals removal and gypsum precipitation by (1) performing surface-aging and solubility calculations in PHREEQC and (2) using the GoldSim framework to direct supernatant and precipitate to subsequent process steps. Users can apply this modeling framework to predict effluent water quality, chemical requirements, sludge production, and required equipment capacity to support design, troubleshooting, and cost estimating. INTRODUCTION Design of effective mine water treatment plants depends on the ability to reliably predict treatment outcomes, but systems with multiple chemical and physical treatment processes and recycle loops can be difficult to model. GoldPHREEQC is a modeling framework that integrates mass and flow routing capabilities of GoldSim software (1) and water quality calculations provided by PHREEQC (2), and is well-suited to modeling treatment of parameters of interest in the mining industry, especially metals and sulfate. GoldPHREEQC can also be applied to other water treatment scenarios using inorganic reactions and processes. The GoldPHREEQC model framework moves water and mass between specified model nodes and calculates specified reaction and water quality outcomes. It can be organized to provide flow, load, and concentration information for each location, including effluent and byproduct streams, and outputs can be adapted to include power and chemical costs."

Jan 1, 2018

By D. Bleazard

Barrick Goldstrike Mines, Inc. is actively involved in improving the reliability of mining and processing equipment through the use of failure analysis and condition monitoring activities. Program results include an increase in equipment capacity and an overall reduction in operating costs. The identification of equipment failure modes and the development of associated capital asset management practices can minimize failure consequences. Successful programs have included; alterations to management practices, equipment modifications, and/or the implementation of condition monitoring programs. By controlling or minimizing the effects of incipient equipment failures, corrective actions can be taken earlier in the failure cycle, resulting in an associated reduction to repair costs and equipment down time.

Jan 1, 1997

By Joseph Alexis

Humphreys Engineering Co. has been associated with mining and milling since the turn of the century, but its greatest contribution to the industry was development of the Humphreys spiral concentrator in 1943. Few devices in the history of mineral beneficiation have been so uncomplicated. The spiral concentrator has no moving parts and requires no power except that needed to deliver slurry to the feed box, a requirement common to all concentrating devices. Although Humphreys Engineering Co. produces several models of spiral concentrators, the one -commonly used for coal cleaning is Model 24C-6 which has a flatter pitch than most other models. The spiral concentrator consists of a spiral conduit with a modified semicircular cross section. A slurry containing 20-35% solids by weight is fed to the feed box at the top of the spiral and flows downward. The heavier refuse particles concentrate along the inner side of the slurry stream and the lighter coal moves to the outside. The coal spiral has six complete turns-each turn consists of three 120°-sections and each section has a refuse port at the lowest point of the channel. The Humphreys spiral concentrator separates minerals in accordance with their physical properties (primarily specific gravity and particle shape). Aside from pumping slurry to the distributor, no energy is required to produce clean coal since the separating action is controlled by gravity. As slurry flows down the spiral channel, each particle is subjected to a centrifugal force, tangential to the channel. This force piles slurry on the outer rim of the spiral until the flowing stream reaches an equilibrium between outward centrifugal force and downward gravitational force. Once established, the stream position is relatively constant. In any flowing stream, differential velocities are present within that stream (the slowest fluid levels nearest the channel surface and the fastest layers at the center). As the channel curves, the lower slurry levels, retarded by friction, have much less centrifugal force and tend to move sideways toward the inner radius of the channel. As the bottom layers move inward along the bottom of the channel, the upper layers must move outward to maintain equilibrium. This cross sectional rotation separates the minerals and moves those of highest specific gravity toward the inner radius where they drop through refuse ports (see figure on following page). The simplicity of the spiral concentrator is apparent in operation. After tonnage, slurry volume, and percent solids of the feed have been determined-generally with laboratory testing-the operator's main concern is simple adjustment of the splitters located in the refuse ports. These splitters control the amount of refuse collected and, generally, once properly set they need little attention unless grade conditions drastically change or trash builds up and hinders laminar flow. Spiral concentrators are not overly sensitive to changes in pulp densities, variances in grade, or parti¬cle size and shapes. All these conditions may fluctuate over fairly wide ranges without adversely affecting recovery and product grade. In certain applications, desliming may improve recovery.

Jan 8, 1980

By Edwin H. Bentzen, Immo H. Redeker

Important industrial minerals are separated and concentrated by froth flotation by industry today. The following descriptions are presented as an overview of the methods employed to separate and recover a few of these industrial minerals. The minerals described in this section of the book are not, by any means, the only important minerals treated by froth flotation. Other minerals, such as calcite, kaolin, wollastonite, rare earths and vermiculite were not included, primarily due to the confidential nature of the information held by the Minerals Research Laboratory and the Colorado School of Mines Research Institute. Flotation of nonmetallic minerals is sometimes viewed as alchemy. However, the art is, in reality, based on sound chemistry, experience and a little luck in the treatment of new ores. In the flotation of nonmetallic minerals, as opposed to base metal sulfides, highly specific treatment conditions are required to accomplish separations. The presentation of the treatment of each of the minerals described was outlined as follows: DEPOSITS PROCESSING SPECIFICATIONS FLOWSHEETS (in some cases) A presentation of the factors, often critical, which must be carefully investigated to accomplish successful flotation of nonmetallic minerals is presented in the section on Sulfonate Collectors, elsewhere in this volume.

Jan 1, 1986

By Rebecca S. Stanevich

BACKGROUND Diesel exhaust is an animal carcinogen, although evidence of the carcinogenicity in humans is "limited". (World Health Org. , 1989) Of the eight cohort studies in the 19808, five found an increased risk for lung cancer among workers who may have been exposed to diesel exhaust (RR from 1.3-1.5, SMR from 101-132). (Howe, et al., 1983) Only two studies accounted for smoking indirectly. Of the ten case-control studies in the 1980's, eight reported increased risk of lung cancer among those populations purportedly exposed to diesel exhaust. (Benhamou, et al. , 1988) All but one of these adjusted for smoking and other occupational exposures. The odds ratios ranged from 1.2 to 2.1. In two of these studies, miners experienced a two to three fold risk. (Benhamou, et al., 1988) Bladder cancer has also been linked to diesel exhaust in cohort and case-control studies. Excesses of approximately 50% were observed among truck drivers in studies by NCI. (Hoar, et al., 1985) In the National Bladder Cancer Study, risks for truck drivers rose with duration of employment. A study by NIOSH in Ohio also found an excess of bladder cancer among truck drivers, particularly among those with 20 or more years of employment. (Steenland, et al, 1987) Despite the large number of studies in which the relation between diesel exhaust exposure and lung cancer has been examined, exposure to diesel exhaust has been quantitatively estimated only in the studies of railroad workers and truck drivers. (Woskie, et al., 1988) The excess lung cancer risk experienced by workers in these two occupational groups was modest, ranging from 40 to 90% for those with long-term employment. However, diesel exhaust exposure among railroad workers and truck drivers is lower than that seen among miners. Several markers of diesel exhaust have been utilized in these studies. Diesel exhaust is a complex mixture of particulates, vapors and gases. One group of these gases, the nitrogen oxides, react with polynuclear aromatic hydrocarbons, forming mutagenic and possible carcinogenic nitrated derivatives. (World Health Organization, 1989) For this reason, and because it is easy to measure and analyze, NO, was frequently used as a marker of diesel exhaust exposure. As part of the Garshick (Garshick, et al., 1988) study of railroad workers, Woskie measured NO, exposures of 477 railroad workers. (Woskie, et al., 1988) Geometric mean exposures of 13 job groups ranged from 12 to 80 ppb. In a New Mexico potash mine, (Attfield, et al. , 1982) exposures of from 100 to 3300 ppb nitrogen dioxide

Jan 1, 1992

By L. L. Anderson

Western bituminous coal can be processed to low sulfur liquid fuels by fast reactions. A process (LEFCO) under development at the University of Utah uses coal and catalyst under hydrogen pressure to convert 60 to 70 percent of the coal matter to fuel liquids and gases. Coals have been processed in small diameter (less than 1/2 inch) tubes and at reaction residence times of less than 10 seconds. Effects of process variables on the yield and quality of products have been studied. General features of the process and the properties and characteristics of the products produced are presented. Special features of the process that distinguish it from other liquefaction processes under development are also discussed.

Jan 1, 1975

By K. Luxbacher, D. T. Hristopulos, S. Schafrik, J. Diaz, Z. Agioutantis

Big data is generated from both surface and underground mining operations. Such data contain a wealth of information concerning safety and health in the workplace and production parameters. This paper will discuss the progress towards developing an accurate forecasting model for methane gas concentration based on the analysis of data collected from Atmospheric Monitoring Systems in underground coal mines employing time series models. Several procedures need to be applied to raw data, such as data cleaning and filtering for outlier removal, data homogenization and segmentation, and exploratory statistical analysis. The data analyzed were retrieved from two coal operations in the Eastern US. A negative correlation between barometric pressure and methane gas concentration was established, at least for certain data segments. Such correlations raise the possibility that barometric pressure data can predict variations of gas concentration in the mine. The datasets will be further investigated to establish the robustness of barometric pressure and gas concentration correlation and explore the dependence of gas concentration on other factors related to mine design and operations

Mar 2, 2022